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ontocord/Dolci-Instruct-DPO-decontaminated

published by @ontocord

Alignment dataset tracked in the /datasets sub-catalog.

Lifetime downloads
295
Last 30 days
19
Likes
-
Size
757.2 MB
Created on HF
2026-03-06
Age
7 months ago

Description

Dolci-Instruct-DPO-decontaminated

Decontaminated version of allenai/Dolci-Instruct-DPO.

Decontamination Details

Method: 13-gram overlap detection

Original samples: 259,922

Cleaned samples: 258,349

Removed samples: 1,573 (0.61%)

Benchmarks Checked

MMLU, Ifeval, ARC, COPA, LAMBADA, OpenBookQA, Winogrande, BoolQ, HellaSwag, PIQA, Gsm8k, ALERT, GPQA, MATH, MBPP, HumanEval, SimpleQA, CommonsenseQA, DoNotAnswer, AIME24, LiveCodeBench, MATH500

Tags

license:apache-2.0size_categories:100K<n<1Mformat:parquetmodality:textlibrary:datasetslibrary:dasklibrary:polarslibrary:mlcroissantregion:usdecontaminated

README current version from Hugging Face

dataset_info:
config_name: default
splits:
- name: train
num_examples: 258349
license: apache-2.0
tags:

  • decontaminated

Dolci-Instruct-DPO-decontaminated

Decontaminated version of allenai/Dolci-Instruct-DPO.

Decontamination Details

  • Method: 13-gram overlap detection
  • Original samples: 259,922
  • Cleaned samples: 258,349
  • Removed samples: 1,573 (0.61%)

Benchmarks Checked

MMLU, Ifeval, ARC, COPA, LAMBADA, OpenBookQA, Winogrande, BoolQ, HellaSwag, PIQA, Gsm8k, ALERT, GPQA, MATH, MBPP, HumanEval, SimpleQA, CommonsenseQA, DoNotAnswer, AIME24, LiveCodeBench, MATH500

README history 5 revisions

Every night we snapshot the README of every dataset in the catalog. When the SHA changes we archive the new version and diff it against the last. This is the evolving thought record of the alignment-data field: what the author decided to say about the corpus, and how that framing shifted over time.

  1. 2026-03-06Upload README.md with huggingface_hub1133535685 B
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  2. 2026-03-06Upload scan_summary.json with huggingface_hub1a8fdc80 B
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  3. 2026-03-06Upload decontamination_summary.json with huggingface_huba43f7d10 B
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  4. 2026-03-06Upload folder using huggingface_hubd07afa90 B
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  5. 2026-03-06initial commitf7402c50 B
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Used by abliterated models none yet

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Read further

Community best practices (architecture)
4 rules for MoE, hybrid SSM, FP8 requantization, and Gemma quirks.
The six workflow stages
What misc is doing more work than its name suggests.
Beyond English: multilingual corpora
The four language communities and their workarounds.
Non-English abliteration communities
Deep dive: huihui-ai, layer-window, slop-framing, CJK tokenizer fixes.

Metadata

License
apache-2.0

Repository

DIR data 5 files FILE .gitattributes FILE decontamination_summary.json FILE README.md FILE scan_summary.json

File contents live on Hugging Face. Click a file or folder to open it there.

Download the dataset

Gated dataset. You need to accept the author's terms on Hugging Face before downloading. Visit the repository, click Agree and access repository, then log in locally with huggingface-cli login and use one of the snippets below.

Copy any of these snippets into your notebook or terminal. All three fetch directly from Hugging Face using your own credentials.

Recommended: datasets library (Python) 
from datasets import load_dataset
ds = load_dataset("ontocord/Dolci-Instruct-DPO-decontaminated")
Raw snapshot (Python) 
from huggingface_hub import snapshot_download
snapshot_download(repo_id="ontocord/Dolci-Instruct-DPO-decontaminated", repo_type="dataset")
git clone (requires git-lfs) 
git clone https://huggingface.co/datasets/ontocord/Dolci-Instruct-DPO-decontaminated
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